Tianjiao Dai

874 total citations · 1 hit paper
33 papers, 540 citations indexed

About

Tianjiao Dai is a scholar working on Mechanics of Materials, Control and Systems Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Tianjiao Dai has authored 33 papers receiving a total of 540 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Mechanics of Materials, 8 papers in Control and Systems Engineering and 8 papers in Electrical and Electronic Engineering. Recurrent topics in Tianjiao Dai's work include Mechanical stress and fatigue analysis (7 papers), Machine Fault Diagnosis Techniques (5 papers) and Adhesion, Friction, and Surface Interactions (4 papers). Tianjiao Dai is often cited by papers focused on Mechanical stress and fatigue analysis (7 papers), Machine Fault Diagnosis Techniques (5 papers) and Adhesion, Friction, and Surface Interactions (4 papers). Tianjiao Dai collaborates with scholars based in China, Norway and Taiwan. Tianjiao Dai's co-authors include Svein Sævik, Yushi Tang, Bei Huang, Yan Zhang, Yaohui Bai, Yile Tao, Donghui Wen, Yufen Zhang, Xiaohui Bi and Qili Dai and has published in prestigious journals such as Applied Physics Letters, Chemistry of Materials and The Science of The Total Environment.

In The Last Decade

Tianjiao Dai

29 papers receiving 535 citations

Hit Papers

Revealing Drivers of Haze Pollution by Explainable Machin... 2022 2026 2023 2024 2022 50 100 150
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Revealing Drivers of Haze Pollution by Explainable Machine Learning
    2022 156 citations Qili Dai, Congbo Song et al. Environmental Science & Technology Letters profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Tianjiao Dai China 10 131 125 107 89 84 33 540
Bryan Willson United States 17 36 0.3× 119 1.0× 66 0.6× 100 1.1× 27 0.3× 50 1.3k
Xuemei China 12 105 0.8× 30 0.2× 95 0.9× 85 1.0× 36 0.4× 112 662
S. Dasgupta China 13 73 0.6× 18 0.1× 37 0.3× 62 0.7× 115 1.4× 43 901
Zhenyu 13 47 0.4× 18 0.1× 44 0.4× 59 0.7× 59 0.7× 118 753
Jianhui 13 56 0.4× 31 0.2× 47 0.4× 80 0.9× 29 0.3× 72 512
Jinwen Li China 17 142 1.1× 49 0.4× 191 1.8× 14 0.2× 30 0.4× 52 1.0k
Zhenrui Zhang China 16 62 0.5× 31 0.2× 65 0.6× 18 0.2× 103 1.2× 42 727
Pengfei Liu China 13 148 1.1× 103 0.8× 153 1.4× 18 0.2× 26 0.3× 37 580

Countries citing papers authored by Tianjiao Dai

Since Specialization
Citations

This map shows the geographic impact of Tianjiao Dai's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tianjiao Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tianjiao Dai more than expected).

Fields of papers citing papers by Tianjiao Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tianjiao Dai. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tianjiao Dai. The network helps show where Tianjiao Dai may publish in the future.

Co-authorship network of co-authors of Tianjiao Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Tianjiao Dai. A scholar is included among the top collaborators of Tianjiao Dai based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tianjiao Dai. Tianjiao Dai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Dai, Tianjiao, et al.. (2025). Isogeometric contact analysis in subsea umbilical and power cables. Marine Structures. 106. 103960–103960.
2.
Wu, Jun, et al.. (2025). Source-free domain adaptation framework for rotating machinery fault diagnosis by reliable self-learning and auxiliary contrastive learning. Reliability Engineering & System Safety. 262. 111228–111228. 4 indexed citations
3.
4.
Tian, Ge, Ruihuan Zhang, Mengying Zhao, et al.. (2025). Biogeochemical stratification governs microbial hydrocarbon degradation potential in a petrochemical contaminated site. Environmental Research. 285(Pt 1). 122286–122286.
5.
Xie, Jiajun, et al.. (2025). Finite element study on the wet collapse mechanism of a flexible pipe with eroded carcass. Ocean Engineering. 329. 121124–121124. 1 indexed citations
6.
7.
Dai, Tianjiao, et al.. (2024). New Bounds for Odd Colourings of Graphs. The Electronic Journal of Combinatorics. 31(4).
8.
Gao, Zhan, et al.. (2024). Nonlinear slow-varying dynamics-assisted temporal graph transformer network for remaining useful life prediction. Reliability Engineering & System Safety. 248. 110162–110162. 20 indexed citations
9.
Wu, Jun, et al.. (2024). Multilayer Fused Correntropy Reprsenstation for Fault Diagnosis of Mechanical Equipment. Sensors. 24(18). 6142–6142. 1 indexed citations
10.
Dai, Tianjiao, Qili Dai, Jiajia Chen, et al.. (2024). Spatial source apportionment of airborne coarse particulate matter using PMF-Bayesian receptor model. The Science of The Total Environment. 917. 170235–170235. 7 indexed citations
11.
Dai, Tianjiao, Qili Dai, Jing Ding, et al.. (2023). Measuring the Emission Changes and Meteorological Dependence of Source‐Specific BC Aerosol Using Factor Analysis Coupled With Machine Learning. Journal of Geophysical Research Atmospheres. 128(15). 12 indexed citations
12.
Dai, Qili, Congbo Song, Bowen Liu, et al.. (2022). Revealing Drivers of Haze Pollution by Explainable Machine Learning. Environmental Science & Technology Letters. 9(2). 112–119. 156 indexed citations breakdown →
13.
14.
Li, Pengjie, et al.. (2021). An efficient fatigue analysis for the nonbonded flexible riser. Ships and Offshore Structures. 17(10). 2238–2253. 5 indexed citations
15.
Dai, Tianjiao, et al.. (2020). Charge Detrapping on Gate Edge of AlGaN/GaN HEMT Under Drain Stress. 1–3. 1 indexed citations
16.
Dai, Tianjiao, et al.. (2017). Friction models for evaluating dynamic stresses in non-bonded flexible risers. Marine Structures. 55. 137–161. 29 indexed citations
17.
Dai, Tianjiao, Yan Zhang, Yushi Tang, et al.. (2016). Identifying the key taxonomic categories that characterize microbial community diversity using full-scale classification: a case study of microbial communities in the sediments of Hangzhou Bay. FEMS Microbiology Ecology. 92(10). fiw150–fiw150. 117 indexed citations
18.
Dai, Tianjiao, et al.. (2016). Comparison study of umbilicals' curvature based on full scale tests and numerical models. The 26th International Ocean and Polar Engineering Conference. 1 indexed citations
19.
Wang, Howard, et al.. (2015). Effect of Surface Contact Stiffness on Stress Analysis of Umbilicals. The Twenty-fifth International Ocean and Polar Engineering Conference. 2 indexed citations
20.
Shao, Naimin, et al.. (2014). Evidence of guest encapsulation within G8 and G10 dendrimers using NMR techniques. Soft Matter. 10(45). 9153–9158. 7 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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